Separable distortion disparity determination

ABSTRACT

Systems and methods for determining disparity between two images are disclosed. Such systems and methods include obtaining a first raw pixel image of a scene from a first viewpoint, obtaining a second raw pixel image of the scene from a second viewpoint (e.g., separate from the first viewpoint in a camera baseline direction such as horizontal or vertical), modifying the first and second raw pixel images using component-separated correction to create respective first and second corrected pixel images maintaining pixel scene correspondence in the camera baseline direction from between the first and second raw pixel images to between the first and second corrected pixel images, determining pixel pairs from corresponding pixels between the first and second corrected pixel images in the camera baseline direction, and determining disparity correspondence for each of the determined pixel pairs from pixel locations in the first and second raw pixel images corresponding to respective pixel locations of the pixel pairs in the first and second corrected pixel images.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application claims priority to U.S. Provisional application Ser.No. 62/737,281 entitled Separable Distortion Disparity Determination,filed on Sep. 27, 2018, the contents of which are incorporated fullyherein by reference.

TECHNICAL FIELD

The present subject matter relates to electronic devices, e.g., eyeweardevices, and mobile devices and techniques to determine disparity, e.g.for creating and presenting three dimensional images.

BACKGROUND

Electronic devices, such as wearable devices, including portable eyeweardevices (e.g., smartglasses, headwear, and headgear); mobile devices(e.g., tablets, smartphones, and laptops); and personal computersavailable today integrate image displays and cameras.

Wearable device may include multiple cameras for gathering imageinformation from a scene. The lenses of the one or more cameras cancause the image to be distorted. Such distortion interferes with theability to accurately reproduce the scene on a display. Methods andsystems for accurately presenting images are desirable.

BRIEF DESCRIPTION OF THE DRAWINGS

The drawing figures depict one or more implementations, by way ofexample only, not by way of limitations. In the figures, like referencenumerals refer to the same or similar elements.

FIG. 1A is a right side view of an example hardware configuration of aneyewear device utilized in a separable distortion disparitydetermination system;

FIG. 1B is a top cross-sectional view of a right chunk of the eyeweardevice of FIG. 1A depicting a right visible light camera, and a circuitboard;

FIG. 1C is a left side view of an example hardware configuration of theeyewear device of FIG. 1A, which shows a left visible light camera;

FIG. 1D is a top cross-sectional view of a left chunk of the eyeweardevice of FIG. 1C depicting the left visible light camera, and a circuitboard.

FIGS. 2A and 2B are rear views of example hardware configurations of aneyewear device utilized in the separable distortion disparitydetermination system, including two different types of image displays;

FIG. 3 depicts an example of visible light captured by the left visiblelight camera as a left raw image and visible light captured by the rightvisible light camera as a right raw image;

FIG. 4 is a functional block diagram of an example separable distortiondisparity determination system including the eyewear device, a mobiledevice, and a server system connected via various networks;

FIG. 5 shows an example of a hardware configuration for the mobiledevice of the separable distortion disparity determination system ofFIG. 4;

FIG. 6 is a flowchart of an example method for separable distortiondisparity determination, generation and presentation of threedimensional image with corrected images;

FIG. 7 is a flow chart of example steps for determining disparitycorrespondence in the example method of FIG. 6;

FIGS. 8A and 8B are representative illustrations of raw image pairs of ascene (FIG. 10A) and corrected image pairs (FIG. 10B) produced duringthe method of FIG. 6;

FIG. 9 is a representative illustration of determining disparitycorrespondence between the raw image pairs and the separable distortionimage pairs during the method of FIG. 6; and

FIGS. 10A and 10B depict examples of a raw image and a correspondingcorrected image, respectively.

DETAILED DESCRIPTION

In the following detailed description, numerous specific details are setforth by way of examples in order to provide a thorough understanding ofthe relevant teachings. However, it should be apparent to those skilledin the art that the present teachings may be practiced without suchdetails. In other instances, description of well-known methods,procedures, components, and circuitry are set forth at a relativelyhigh-level, without detail, in order to avoid unnecessarily obscuringaspects of the present teachings.

The term “coupled” or “connected” as used herein refers to any logical,optical, physical or electrical connection, link or the like by whichelectrical or magnetic signals produced or supplied by one systemelement are imparted to another coupled or connected element. Unlessdescribed otherwise, coupled or connected elements or devices are notnecessarily directly connected to one another and may be separated byintermediate components, elements or communication media that maymodify, manipulate or carry the electrical signals. The term “on” meansdirectly supported by an element or indirectly supported by the elementthrough another element integrated into or supported by the element.

The orientations of the eyewear device, associated components and anycomplete devices incorporating a three-dimensional camera such as shownin any of the drawings, are given by way of example only, forillustration and discussion purposes. In operation for separabledistortion disparity determination in an image, the eyewear device maybe oriented in any other direction suitable to the particularapplication of the eyewear device, for example up, down, sideways, orany other orientation. Also, to the extent used herein, any directionalterm, such as front, rear, inwards, outwards, towards, left, right,lateral, longitudinal, up, down, upper, lower, top, bottom, side,horizontal, vertical, and diagonal are used by way of example only, andare not limiting as to direction or orientation of any three-dimensionalcamera or component of the three-dimensional camera constructed asotherwise described herein.

Additional objects, advantages and novel features of the examples willbe set forth in part in the following description, and in part willbecome apparent to those skilled in the art upon examination of thefollowing and the accompanying drawings or may be learned by productionor operation of the examples. The objects and advantages of the presentsubject matter may be realized and attained by means of themethodologies, instrumentalities and combinations particularly pointedout in the appended claims.

Reference now is made in detail to the examples illustrated in theaccompanying drawings and discussed below.

FIG. 1A is a right side view of an example hardware configuration of aneyewear device 100 utilized in separable distortion disparitydetermination system, which shows a right visible light camera 114B forgathering image information. As further described below, in theseparable distortion disparity determination system, two cameras captureimage information for a scene from two separate viewpoints. The twocaptured images are modified to generate two corrected images, pixelpairs are determined between the two corrected images in a camerabaseline direction and a disparity correspondence is determined for eachof the pixel pairs.

Eyewear device 100, includes a right optical assembly 180B with an imagedisplay to present images, such as depth images. As shown in FIGS. 1A-B,the eyewear device 100 includes the right visible light camera 114B.Eyewear device 100 can include multiple visible light cameras 114A-Bthat form a passive type of three-dimensional camera, such as stereocamera, of which the right visible light camera 114B is located on aright chunk 110B. As shown in FIGS. 1C-D, the eyewear device 100 alsoincludes a left visible light camera 114A.

Left and right visible light cameras 114A-B are sensitive to the visiblelight range wavelength. Each of the visible light cameras 114A-B have adifferent frontward facing field of view which are overlapping to enablegeneration of three-dimensional depth images, for example, right visiblelight camera 114B depicts a right field of view 111B. Generally, a“field of view” is the part of the scene that is visible through thecamera at a particular position and orientation in space. The fields ofview 111A and 11B have an overlapping field of view 813. Objects orobject features outside the field of view 111A-B when the visible lightcamera captures the image are not recorded in a raw image (e.g.,photograph or picture). The field of view describes an angle range orextent, which the image sensor of the visible light camera 114A-B picksup electromagnetic radiation of a given scene in a captured image of thegiven scene. Field of view can be expressed as the angular size of theview cone, i.e., an angle of view. The angle of view can be measuredhorizontally, vertically, or diagonally.

In an example, visible light cameras 114A-B have a field of view with anangle of view between 15° to 30°, for example 24°, and have a resolutionof 480×480 pixels. The “angle of coverage” describes the angle rangethat a lens of visible light cameras 114A-B or infrared camera 220 (seeFIG. 2A) can effectively image. Typically, the camera lens produces animage circle that is large enough to cover the film or sensor of thecamera completely, possibly including some vignetting toward the edge.If the angle of coverage of the camera lens does not fill the sensor,the image circle will be visible, typically with strong vignettingtoward the edge, and the effective angle of view will be limited to theangle of coverage.

Examples of such visible lights camera 114A-B include a high-resolutioncomplementary metal-oxide-semiconductor (CMOS) image sensor and a videographic array (VGA) camera, such as 640p (e.g., 640×480 pixels for atotal of 0.33 megapixels), 720p, or 1080p. As used herein, the term“overlapping” when referring to field of view means the matrix of pixelsin the generated raw image(s) overlap by 30% or more. As used herein,the term “substantially overlapping” when referring to field of viewmeans the matrix of pixels in the generated raw image(s) or infraredimage of a scene overlap by 50% or more.

The eyewear device 100 may capture image sensor data from the visiblelight cameras 114A-B along with geolocation data, digitized by an imageprocessor, for storage in a memory. The left and right raw imagescaptured by respective visible light cameras 114A-B are in thetwo-dimensional space domain and comprise a matrix of pixels on atwo-dimensional coordinate system that includes an X-axis for horizontalposition and a Y-axis for vertical position. Each pixel includes a colorattribute value (e.g., a red pixel light value, a green pixel lightvalue, and/or a blue pixel light value); and a position attribute (e.g.,an X location coordinate and a Y location coordinate).

To provide stereoscopic vision, an image processor (element 912 of FIG.4) may couple to visible light cameras 114A-B to receive imageinformation for digital processing along with a timestamp in which theimage of the scene is captured. Image processor 912 includes circuitryto receive signals from the visible light cameras 114A-B and processthose signals from the visible light camera 114 into a format suitablefor storage in the memory. The timestamp can be added by the imageprocessor or other processor, which controls operation of the visiblelight cameras 114A-B. Visible light cameras 114A-B allow thethree-dimensional camera to simulate human binocular vision.Three-dimensional camera provides the ability to reproducethree-dimensional images based on two captured images from the visiblelight cameras 114A-B having the same timestamp. Such three-dimensionalimages allow for an immersive life-like experience, e.g., for virtualreality or video gaming.

For stereoscopic vision, a pair of raw red, green, and blue (RGB) imagesare captured of a scene at a given moment in time—one image for each ofthe left and right visible light cameras 114A-B. When the pair ofcaptured raw images from the frontward facing left and right field ofviews 111A-B of the left and right visible light cameras 114A-B areprocessed (e.g., by the image processor), depth images are generated,and the generated depth images, which a user perceives on an opticalassembly 180A-B or other image display(s) (e.g., of a mobile device).The generated depth images are in the three-dimensional space domain andcan comprise a matrix of vertices on a three-dimensional locationcoordinate system that includes an X axis for horizontal position (e.g.,length), a Y axis for vertical position (e.g., height), and a Z axis fordepth (e.g., distance). Each vertex includes a color attribute value(e.g., a red pixel light value, a green pixel light value, and/or a bluepixel light value); a position attribute (e.g., an X locationcoordinate, a Y location coordinate, and a Z location coordinate); atexture attribute, and/or a reflectance attribute. The texture attributequantifies the perceived texture of the depth image, such as the spatialarrangement of color or intensities in a region of vertices of the depthimage.

Generally, perception of depth arises from the disparity of a given 3Dpoint in the left and right raw images captured by visible light cameras114A-B. Disparity is the difference in image location of the same 3Dpoint when projected under perspective of the visible light cameras114A-B (d=x_(left)−x_(right)). For visible light cameras 114A-B withparallel optical axes, focal length f, baseline b, and correspondingimage points (x_(left), y_(left)) and (x_(right), y_(right)), thelocation of a 3D point (Z axis location coordinate) can be derivedutilizing triangulation which determines depth from disparity.Typically, depth of the 3D point is inversely proportional to disparity.A variety of other techniques can also be used. Generation ofthree-dimensional depth images is explained in more detail below.

In an example, a separable disparity distortion determination systemincludes the eyewear device 100. The eyewear device 100 includes a frame105 and a left temple 110A extending from a left lateral side 170A ofthe frame 105 and a right temple 110B extending from a right lateralside 170B of the frame 105. Eyewear device 100 further includes twocameras. The two cameras may include at least two visible light cameraswith overlapping fields of view. In one example, the two camerasincludes a left visible light camera 114A with a left field of view 111Aconnected to the frame 105 or the left temple 110A to capture a leftimage of the scene. Eyewear device 100 further includes a right visiblelight camera 114B connected to the frame 105 or the right temple 110Bwith a right field of view 111B to capture (e.g., simultaneously withthe left visible light camera 114A) a right image of the scene whichpartially overlaps the left image.

The separable disparity distortion determination system further includesa computing device, such as a host computer (e.g., mobile device 990 ofFIG.4) coupled to eyewear device 100 over a network. The separabledisparity distortion determination system, further includes an imagedisplay (optical assembly 180A-B of eyewear device; image display 180 ofmobile device 990 of FIG. 4) for presenting (e.g., displaying) athree-dimensional depth image Separable disparity distortiondetermination system further includes an image display driver (element942 of eyewear device 100 of FIG. 4; element 1090 of mobile device 990of FIG. 4) coupled to the image display (optical assembly 180A-B ofeyewear device; image display 1080 of mobile device 990 of FIG. 5) tocontrol the image display to present the depth image.

Separable disparity distortion determination system further includes auser input device to receive a two-dimensional input selection from auser. Examples of user input devices include a touch sensor (element 991of FIG. 4 for the eyewear device 100), a touch screen display (element1091 of FIG. 5 for the mobile device 990 of FIG. 5), and a computermouse for a personal computer or a laptop computer. The separabledisparity distortion determination system further includes a processor(element 932 of eyewear device 100 of FIG. 4; element 1030 of the mobiledevice 990 of FIG. 5) coupled to the eyewear device 100 and thethree-dimensional camera. The separable disparity distortiondetermination system further includes a memory (element 934 of eyeweardevice 100 of FIG. 4; elements 1040A-B of mobile device 990 of FIG. 4)accessible to the processor, and separable distortion disparitydetermination programming in the memory (element 945 of eyewear device100 of FIG. 4; element 945 of mobile device 990 of FIG. 4), for examplein the eyewear device 100 itself, mobile device (element 990 of FIG. 4),or another part of the separable disparity distortion determinationsystem (e.g., server system 998 of FIG. 4). Execution of the programming(element 945 of FIG. 4) by the processor (element 932 of FIG. 4)configures the eyewear device 100 to generate, via the three-dimensionalcamera, the depth image 961. The depth image includes a matrix ofvertices. Each vertex represents a pixel in a three-dimensional scene.Each vertex has a position attribute. The position attribute of eachvertex is based on a three-dimensional location coordinate system andincludes an X location coordinate on an X-axis for horizontal position,a Y location coordinate on a Y-axis for vertical position, and a Zlocation coordinate on a Z-axis for depth.

Execution of the separable distortion determination programming (element945 of FIG. 4) by the processor (element 1030 of FIG. 5) configures themobile device (element 990 of FIG. 4) of the separable distortiondetermination system to perform the functions described herein.

FIG. 1B is a top cross-sectional view of a right chunk 110B of theeyewear device 100 of FIG. 1A depicting the right visible light camera114B of the camera system, and a circuit board. FIG. 1C is a left sideview of an example hardware configuration of an eyewear device 100 ofFIG. 1A, which shows a left visible light camera 114A of the camerasystem. FIG. 1D is a top cross-sectional view of a left chunk 110A ofthe eyewear device of FIG. 1C depicting the left visible light camera114A of the three-dimensional camera, and a circuit board. Constructionand placement of the left visible light camera 114A is substantiallysimilar to the right visible light camera 114B, except the connectionsand coupling are on the left lateral side 170A. As shown in the exampleof FIG. 1B, the eyewear device 100 includes the right visible lightcamera 114B and a circuit board, which may be a flexible printed circuitboard (PCB) 140B. The right hinge 226B connects the right chunk 110B toa right temple 125B of the eyewear device 100. In some examples,components of the right visible light camera 114B, the flexible PCB140B, or other electrical connectors or contacts may be located on theright temple 125B or the right hinge 226B.

The right chunk 110B includes chunk body 211 and a chunk cap, with thechunk cap omitted in the cross-section of FIG. 1B. Disposed inside theright chunk 110B are various interconnected circuit boards, such as PCBsor flexible PCBs, that include controller circuits for right visiblelight camera 114B, microphone(s), low-power wireless circuitry (e.g.,for wireless short range network communication via Bluetooth™),high-speed wireless circuitry (e.g., for wireless local area networkcommunication via WiFi).

The right visible light camera 114B is coupled to or disposed on theflexible PCB 240 and covered by a visible light camera cover lens, whichis aimed through opening(s) formed in the frame 105. For example, theright rim 107B of the frame 105 is connected to the right chunk 110B andincludes the opening(s) for the visible light camera cover lens. Theframe 105 includes a front-facing side configured to face outwards awayfrom the eye of the user. The opening for the visible light camera coverlens is formed on and through the front-facing side. In the example, theright visible light camera 114B has an outwards facing field of view111B with a line of sight or perspective of the right eye of the user ofthe eyewear device 100. The visible light camera cover lens can also beadhered to an outwards facing surface of the right chunk 110B in whichan opening is formed with an outwards facing angle of coverage, but in adifferent outwards direction. The coupling can also be indirect viaintervening components.

Left (first) visible light camera 114A is connected to a left imagedisplay of left optical assembly 180A to capture a left eye viewed sceneobserved by a wearer of the eyewear device 100 in a left raw image.Right (second) visible light camera 114B is connected to a right imagedisplay of right optical assembly 180B to captured a right eye viewedscene observed by the wearer of the eyewear device 100 in a right rawimage. The left raw image and the right raw image partially overlap topresent a three-dimensional observable space of a generated depth image.

Flexible PCB 140B is disposed inside the right chunk 110B and is coupledto one or more other components housed in the right chunk 110B. Althoughshown as being formed on the circuit boards of the right chunk 110B, theright visible light camera 114B can be formed on the circuit boards ofthe left chunk 110A, the temples 125A-B, or frame 105.

FIGS. 2A-B are rear views of example hardware configurations of theeyewear device 100, including two different types of image displays.Eyewear device 100 is in a form configured for wearing by a user, whichare eyeglasses in the example. The eyewear device 100 can take otherforms and may incorporate other types of frameworks, for example, aheadgear, a headset, or a helmet.

In the eyeglasses example, eyewear device 100 includes a frame 105including a left rim 107A connected to a right rim 107B via a bridge 106adapted for a nose of the user. The left and right rims 107A-B includerespective apertures 175A-B, which hold a respective optical element180A-B, such as a lens and a display device. As used herein, the termlens is meant to cover transparent or translucent pieces of glass orplastic having curved and/or flat surfaces that cause light toconverge/diverge or that cause little or no convergence or divergence.

Although shown as having two optical elements 180A-B, the eyewear device100 can include other arrangements, such as a single optical element ormay not include any optical element 180A-B depending on the applicationor intended user of the eyewear device 100. As further shown, eyeweardevice 100 includes a left chunk 110A adjacent the left lateral side170A of the frame 105 and a right chunk 110B adjacent the right lateralside 170B of the frame 105. The chunks 110A-B may be integrated into theframe 105 on the respective sides 170A-B (as illustrated) or implementedas separate components attached to the frame 105 on the respective sides170A-B. Alternatively, the chunks 110A-B may be integrated into temples(not shown) attached to the frame 105.

In one example, the image display of optical assembly 180A-B includes anintegrated image display. As shown in FIG. 2A, the optical assembly180A-B includes a suitable display matrix 170, such as a liquid crystaldisplay (LCD), an organic light-emitting diode (OLED) display, or anyother such display. The optical assembly 180A-B also includes an opticallayer or layers 176, which can include lenses, optical coatings, prisms,mirrors, waveguides, optical strips, and other optical components in anycombination. The optical layers 176A-N can include a prism having asuitable size and configuration and including a first surface forreceiving light from display matrix and a second surface for emittinglight to the eye of the user. The prism of the optical layers 176A-Nextends over all or at least a portion of the respective apertures175A-B formed in the left and right rims 107A-B to permit the user tosee the second surface of the prism when the eye of the user is viewingthrough the corresponding left and right rims 107A-B. The first surfaceof the prism of the optical layers 176A-N faces upwardly from the frame105 and the display matrix overlies the prism so that photons and lightemitted by the display matrix impinge the first surface. The prism issized and shaped so that the light is refracted within the prism and isdirected towards the eye of the user by the second surface of the prismof the optical layers 176A-N. In this regard, the second surface of theprism of the optical layers 176A-N can be convex to direct the lighttowards the center of the eye. The prism can optionally be sized andshaped to magnify the image projected by the display matrix 170, and thelight travels through the prism so that the image viewed from the secondsurface is larger in one or more dimensions than the image emitted fromthe display matrix 170.

In another example, the image display device of optical assembly 180A-Bincludes a projection image display as shown in FIG. 2B. The opticalassembly 180A-B includes a laser projector 150, which is a three-colorlaser projector using a scanning mirror or galvanometer. Duringoperation, an optical source such as a laser projector 150 is disposedin or on one of the temples 125A-B of the eyewear device 100. Opticalassembly 180-B includes one or more optical strips 155A-N spaced apartacross the width of the lens of the optical assembly 180A-B or across adepth of the lens between the front surface and the rear surface of thelens.

As the photons projected by the laser projector 150 travel across thelens of the optical assembly 180A-B, the photons encounter the opticalstrips 155A-N. When a particular photon encounters a particular opticalstrip, the photon is either redirected towards the user's eye, or itpasses to the next optical strip. A combination of modulation of laserprojector 150, and modulation of optical strips, may control specificphotons or beams of light. In an example, a processor controls opticalstrips 155A-N by initiating mechanical, acoustic, or electromagneticsignals. Although shown as having two optical assemblies 180A-B, theeyewear device 100 can include other arrangements, such as a single orthree optical assemblies, or the optical assembly 180A-B may havearranged different arrangement depending on the application or intendeduser of the eyewear device 100.

As further shown in FIGS. 2A-B, eyewear device 100 includes a left chunk110A adjacent the left lateral side 170A of the frame 105 and a rightchunk 110B adjacent the right lateral side 170B of the frame 105. Thechunks 110A-B may be integrated into the frame 105 on the respectivelateral sides 170A-B (as illustrated) or implemented as separatecomponents attached to the frame 105 on the respective sides 170A-B.Alternatively, the chunks 110A-B may be integrated into temples 125A-Battached to the frame 105.

In one example, the image display includes a first (left) image displayand a second (right) image display. Eyewear device 100 includes firstand second apertures 175A-B which hold a respective first and secondoptical assembly 180A-B. The first optical assembly 180A includes thefirst image display (e.g., a display matrix 170A of FIG. 2A; or opticalstrips 155A-N′ and a projector 150A of FIG. 2B). The second opticalassembly 180B includes the second image display e.g., a display matrix170B of FIG. 2A; or optical strips 155A-N″ and a projector 150B of FIG.2B).

FIG. 3 depicts an example of capturing visible light with the leftvisible light camera 114A and capturing visible light with a rightvisible light camera 114B. Visible light is captured by the left visiblelight camera 114A with a left visible light camera field of view 111A asa left raw image 858A (FIG. 4). Visible light is captured by the rightvisible light camera 114B with a right visible light camera field ofview 111B as a right raw image 858B (FIG.4). Based on processing of theleft raw image 858A (FIG. 4) and the right raw image 858B (FIG. 4), thethree-dimensional depth image of the three-dimensional scene 715 isgenerated as described in greater detail below.

FIG. 4 is a high-level functional block diagram of an example separabledistortion disparity determination system 900, which includes a wearabledevice (e.g., the eyewear device 100), a mobile device 990, and a serversystem 998 connected via various networks. Eyewear device 100 includes athree-dimensional camera, such as at least one of the visible lightcameras 114A-B; and the depth sensor 213, shown as infrared emitter 215and infrared camera 220. The three-dimensional camera can alternativelyinclude at least two visible light cameras 114A-B (one associated withthe left lateral side 170A and one associated with the right lateralside 170B). Three-dimensional camera generates an initial depth image(not shown) of depth image, which are rendered three-dimensional (3D)models that are texture mapped images of a red, green, and blue (RGB)imaged scene.

Mobile device 990 may be a smartphone, tablet, laptop computer, accesspoint, or any other such device capable of connecting with eyeweardevice 100 using both a low-power wireless connection 925 and ahigh-speed wireless connection 937. Mobile device 990 is connected toserver system 998 and network 995. The network 995 may include anycombination of wired and wireless connections.

Eyewear device 100 further includes two image displays of the opticalassembly 180A-B (one associated with the left lateral side 170A and oneassociated with the right lateral side 170B). Eyewear device 100 alsoincludes image display driver 942, image processor 912, low-powercircuitry 920, and high-speed circuitry 930. Image display of opticalassembly 180-B are for presenting images, such as the depth image 961.Image display driver 942 is coupled to the image display of opticalassembly 180A-B to control the image display of optical assembly 180A-Bto present the images, such as the depth image 961. Eyewear device 100further includes a user input device 991 (e.g., touch sensor) to receivea two-dimensional input selection from a user.

The components shown in FIG. 4 for the eyewear device 100 are located onone or more circuit boards, for example a PCB or flexible PCB, in therims or temples. Alternatively or additionally, the depicted componentscan be located in the chunks, frames, hinges, or bridge of the eyeweardevice 100. Left and right visible light cameras 114A-B can includedigital camera elements such as a complementarymetal-oxide-semiconductor (CMOS) image sensor, charge coupled device, alens, or any other respective visible or light capturing elements thatmay be used to capture data, including images of scenes with unknownobjects.

Eyewear device 100 includes a memory 934, which includes separabledistortion disparity determination programming 945 to perform a subset,or all of the functions described herein for determining disparitycorrespondence between two separable distortion images, Flowchartsoutlining functions, which can be implemented in the separabledistortion disparity determination programming 945, is shown in FIGS. 6and 7. As shown, memory 934 further includes a left raw image 858Acaptured by left visible light camera 114A and a right raw imagecaptured by right visible light camera 114B, a left separable distortioncorrected image 808A corresponding to the left raw image, and a rightseparable distortion corrected image 808B corresponding to the right rawimage.

As shown in FIG. 4, high-speed circuitry 930 includes high-speedprocessor 932, memory 934, and high-speed wireless circuitry 936. In theexample, the image display driver 942 is coupled to the high-speedcircuitry 930 and operated by the high-speed processor 932 in order todrive the left and right image displays of the optical assembly 180A-B.High-speed processor 932 may be any processor capable of managinghigh-speed communications and operation of any general computing systemneeded for eyewear device 100. High-speed processor 932 includesprocessing resources needed for managing high-speed data transfers onhigh-speed wireless connection 937 to a wireless local area network(WLAN) using high-speed wireless circuitry 936. In certain embodiments,the high-speed processor 932 executes an operating system such as aLINUX operating system or other such operating system of the eyeweardevice 100 and the operating system is stored in memory 934 forexecution. In addition to any other responsibilities, the high-speedprocessor 932 executing a software architecture for the eyewear device100 is used to manage data transfers with high-speed wireless circuitry936. In certain embodiments, high-speed wireless circuitry 936 isconfigured to implement Institute of Electrical and Electronic Engineers(IEEE) 802.11 communication standards, also referred to herein as Wi-Fi.In other embodiments, other high-speed communications standards may beimplemented by high-speed wireless circuitry 936.

Low-power wireless circuitry 924 and the high-speed wireless circuitry936 of the eyewear device 100 can include short range transceivers(Bluetooth™) and wireless wide, local, or wide area network transceivers(e.g., cellular or WiFi). Mobile device 990, including the transceiverscommunicating via the low-power wireless connection 925 and high-speedwireless connection 937, may be implemented using details of thearchitecture of the eyewear device 100, as can other elements of network995.

Memory 934 includes any storage device capable of storing various dataand applications, including, among other things, camera data generatedby the left and right visible light cameras 114A-B, infrared camera 220,and the image processor 912, as well as images generated for display bythe image display driver 942 on the image displays of the opticalassembly 180A-B. While memory 934 is shown as integrated with high-speedcircuitry 930, in other embodiments, memory 934 may be an independentstandalone element of the eyewear device 100. In certain suchembodiments, electrical routing lines may provide a connection through achip that includes the high-speed processor 932 from the image processor912 or low-power processor 922 to the memory 934. In other embodiments,the high-speed processor 932 may manage addressing of memory 934 suchthat the low-power processor 922 will boot the high-speed processor 932any time that a read or write operation involving memory 934 is needed.

As shown in FIG. 4, the processor 932 of the eyewear device 100 can becoupled to the camera system (visible light cameras 114A-B), the imagedisplay driver 942, the user input device 991, and the memory 934. Asshown in FIG. 5, the processor 1030 of the mobile device 990 can becoupled to the camera system 1070, the image display driver 1090, theuser input device 1091, and the memory 1040A. Eyewear device 100 canperform all or a subset of any of the following functions describedbelow as a result of the execution of the separable distortion disparitydetermination programming 945 in the memory 934 by the processor 932 ofthe eyewear device 100. Mobile device 990 can perform all or a subset ofany of the following functions described below as a result of theexecution of the separable distortion disparity determinationprogramming 945 in the memory 1040A by the processor 1030 of the mobiledevice 990. Functions can be divided in the separable distortiondisparity determination system 900, such that the eyewear device 100captures the images, but the mobile device 990 performs the remainder ofthe image processing.

Server system 998 may be one or more computing devices as part of aservice or network computing system, for example, that include aprocessor, a memory, and network communication interface to communicateover the network 995 with the mobile device 990 and eyewear device 100.Eyewear device 100 is connected with a host computer. For example, theeyewear device 100 is paired with the mobile device 990 via thehigh-speed wireless connection 937 or connected to the server system 998via the network 995.

Output components of the eyewear device 100 include visual components,such as the left and right image displays of optical assembly 180A-B asdescribed in FIGS. 2A-B (e.g., a display such as a liquid crystaldisplay (LCD), a plasma display panel (PDP), a light emitting diode(LED) display, a projector, or a waveguide). The image displays of theoptical assembly 180A-B are driven by the image display driver 942. Theoutput components of the eyewear device 100 further include acousticcomponents (e.g., speakers), haptic components (e.g., a vibratorymotor), other signal generators, and so forth. The input components ofthe eyewear device 100, the mobile device 990, and server system 998,may include alphanumeric input components (e.g., a keyboard, a touchscreen configured to receive alphanumeric input, a photo-opticalkeyboard, or other alphanumeric input components), point-based inputcomponents (e.g., a mouse, a touchpad, a trackball, a joystick, a motionsensor, or other pointing instruments), tactile input components (e.g.,a physical button, a touch screen that provides location and force oftouches or touch gestures, or other tactile input components), audioinput components (e.g., a microphone), and the like.

Eyewear device 100 may optionally include additional peripheral deviceelements. Such peripheral device elements may include biometric sensors,additional sensors, or display elements integrated with eyewear device100. For example, peripheral device elements may include any I/Ocomponents including output components, motion components, positioncomponents, or any other such elements described herein.

For example, the biometric components include components to detectexpressions (e.g., hand expressions, facial expressions, vocalexpressions, body gestures, or eye tracking), measure biosignals (e.g.,blood pressure, heart rate, body temperature, perspiration, or brainwaves), identify a person (e.g., voice identification, retinalidentification, facial identification, fingerprint identification, orelectroencephalogram based identification), and the like. The motioncomponents include acceleration sensor components (e.g., accelerometer),gravitation sensor components, rotation sensor components (e.g.,gyroscope), and so forth. The position components include locationsensor components to generate location coordinates (e.g., a GlobalPositioning System (GPS) receiver component), WiFi or Bluetooth™transceivers to generate positioning system coordinates, altitude sensorcomponents (e.g., altimeters or barometers that detect air pressure fromwhich altitude may be derived), orientation sensor components (e.g.,magnetometers), and the like. Such positioning system coordinates canalso be received over wireless connections 925 and 937 from the mobiledevice 990 via the low-power wireless circuitry 924 or high-speedwireless circuitry 936.

FIG. 5 is a high-level functional block diagram of an example of amobile device 990 that communicates via the separable disparitydistortion determination system 900 of FIG. 4. Mobile device 990includes a user input device 1091 to receive a two-dimensional inputselection. Mobile device 990 also includes a flash memory 1040A, whichincludes separable disparity distortion determination programming 945 toperform all or a subset of the functions described herein. As shown,memory 1040A further includes a left raw image 858A captured by leftvisible light camera 114A and a right raw image captured by rightvisible light camera 114B, a left separable distortion corrected image808A corresponding to the left raw image, a right separable distortionimage 1008B corresponding to the right raw image, a left corrected image1012A corresponding to the left separable distortion image 1008A, and aright separable distortion image 1012B corresponding to the rightseparable distortion image 1008B. Mobile device 1090 can include acamera system 1070 that comprises at least two visible light cameras(first and second visible light cameras with overlapping fields of view)for capturing the left raw image 858A and the right raw image 858B. Whenthe mobile device 990 includes components like the eyewear device 100,such as the camera system, the left raw image 858A and the right rawimage 858B can be captured via the camera system 1070 of the mobiledevice 990.

As shown, the mobile device 990 includes an image display 1080, an imagedisplay driver 1090 to control the image display, and a user inputdevice 1091 similar to the eyewear device 100. In the example of FIG. 5,the image display 1080 and user input device 1091 are integratedtogether into a touch screen display.

Examples of touch screen type mobile devices that may be used include(but are not limited to) a smart phone, a personal digital assistant(PDA), a tablet computer, a laptop computer, or other portable device.However, the structure and operation of the touch screen type devices isprovided by way of example; and the subject technology as describedherein is not intended to be limited thereto. For purposes of thisdiscussion, FIG. 5 therefore provides block diagram illustrations of theexample mobile device 990 having a touch screen display for displayingcontent and receiving user input as (or as part of) the user interface.

As shown in FIG. 5, the mobile device 990 includes at least one digitaltransceiver (XCVR) 1010, shown as WWAN XCVRs, for digital wirelesscommunications via a wide area wireless mobile communication network.The mobile device 990 also includes additional digital or analogtransceivers, such as short range XCVRs 1020 for short-range networkcommunication, such as via NFC, VLC, DECT, ZigBee, Bluetooth™, or WiFi.For example, short range XCVRs 1020 may take the form of any availabletwo-way wireless local area network (WLAN) transceiver of a type that iscompatible with one or more standard protocols of communicationimplemented in wireless local area networks, such as one of the Wi-Fistandards under IEEE 802.11 and WiMAX.

To generate location coordinates for positioning of the mobile device990, the mobile device 990 can include a global positioning system (GPS)receiver. Alternatively, or additionally the mobile device 990 canutilize either or both the short range XCVRs 1020 and WWAN XCVRs 1010for generating location coordinates for positioning. For example,cellular network, WiFi, or Bluetooth™ based positioning systems cangenerate very accurate location coordinates, particularly when used incombination. Such location coordinates can be transmitted to the eyeweardevice over one or more network connections via XCVRs 1010, 1020.

The transceivers 1010, 1020 (network communication interface) conformsto one or more of the various digital wireless communication standardsutilized by modern mobile networks. Examples of WWAN transceivers 1010include (but are not limited to) transceivers configured to operate inaccordance with Code Division Multiple Access (CDMA) and 3rd GenerationPartnership Project (3GPP) network technologies including, for exampleand without limitation, 3GPP type 2 (or 3GPP2) and LTE, at timesreferred to as “4G.” For example, the transceivers 1010, 1020 providetwo-way wireless communication of information including digitized audiosignals, still image and video signals, web page information for displayas well as web related inputs, and various types of mobile messagecommunications to/from the mobile device 990 for separable distortiondisparity determination.

Several of these types of communications through the transceivers 1010,1020 and a network, as discussed previously, relate to protocols andprocedures in support of communications with the eyewear device 100 orthe server system 998 for separable distortion disparity determination,such as transmitting left raw image 858A and right raw image 858B. Suchcommunications, for example, may transport packet data via the shortrange XCVRs 1020 over the wireless connections 925 and 937 to and fromthe eyewear device 100 as shown in FIG. 4. Such communications, forexample, may also transport data utilizing IP packet data transport viathe WWAN XCVRs 1010 over the network (e.g., Internet) 995 shown in FIG.4. Both WWAN XCVRs 1010 and short range XCVRs 1020 connect through radiofrequency (RF) send-and-receive amplifiers (not shown) to an associatedantenna (not shown).

The mobile device 990 further includes a microprocessor, shown as CPU1030, sometimes referred to herein as the host controller. A processoris a circuit having elements structured and arranged to perform one ormore processing functions, typically various data processing functions.Although discrete logic components could be used, the examples utilizecomponents forming a programmable CPU. A microprocessor for exampleincludes one or more integrated circuit (IC) chips incorporating theelectronic elements to perform the functions of the CPU. The processor1030, for example, may be based on any known or available microprocessorarchitecture, such as a Reduced Instruction Set Computing (RISC) usingan ARM architecture, as commonly used today in mobile devices and otherportable electronic devices. Of course, other processor circuitry may beused to form the CPU 1030 or processor hardware in smartphone, laptopcomputer, and tablet.

The microprocessor 1030 serves as a programmable host controller for themobile device 990 by configuring the mobile device 990 to performvarious operations, for example, in accordance with instructions orprogramming executable by processor 1030. For example, such operationsmay include various general operations of the mobile device, as well asoperations related to the separable distortion disparity determinationprogramming 945 and communications with the eyewear device 100 andserver system 998. Although a processor may be configured by use ofhardwired logic, typical processors in mobile devices are generalprocessing circuits configured by execution of programming.

The mobile device 990 includes a memory or storage device system, forstoring data and programming. In the example, the memory system mayinclude a flash memory 1040A and a random access memory (RAM) 1040B. TheRAM 1040B serves as short term storage for instructions and data beinghandled by the processor 1030, e.g., as a working data processingmemory. The flash memory 1040A typically provides longer term storage.

Hence, in the example of mobile device 990, the flash memory 1040A isused to store programming or instructions for execution by the processor1030. Depending on the type of device, the mobile device 990 stores andruns a mobile operating system through which specific applications,including separable distortion disparity determination programming 945,are executed. Applications, such as the separable distortion disparitydetermination programming 945, may be a native application, a hybridapplication, or a web application (e.g., a dynamic web page executed bya web browser) that runs on mobile device 990 to determine separabledistortion disparity. Examples of mobile operating systems includeGoogle Android, Apple iOS (I-Phone or iPad devices), Windows Mobile,Amazon Fire OS, RIM BlackBerry operating system, or the like.

It will be understood that the mobile device 990 is just one type ofhost computer in the separable distortion disparity determination system900 and that other arrangements may be utilized.

FIG. 6 is a flowchart of a method with steps that can be implemented ina separable distortion disparity determination system. To facilitatedescription and understanding the steps of the following flowcharts aredescribed with reference to the systems and apparatus described herein.One of skill in the art will recognize other suitable systems andapparatus for performing the steps described herein. In addition, themethod is described with reference to a camera system that includes twocameras separated in a horizontal direction. In other examples, thecameras may have another orientation with respect to one another (e.g.,separated in a vertical direction).

At step 602, obtain two images of a scene. A processor (e.g., element932 of eyewear device 100 of FIG. 4 or element 1030 of mobile device 990of FIG. 5) obtains images of the scene captured by respective camerashaving different points of view. In an example, a left visible lightcamera 114 a of an eyewear device 100 captures a left raw image(Left_(RAW)) and a right visible light image 114 b of an eyewear device100 captures a right raw image (Right_(RAW)). The cameras are separatedin a camera baseline direction (here in a horizontal direction). FIG. 8Adepicts an illustrative example of a left raw image 858A and a right rawimage 858B of a three dimensional scene 715 including an object 802(i.e., a tree).

At step 604, modify the obtained left and right raw images to createrespective left and right corrected pixel images. The processor maymodify the left and right raw images by applying a component-separatedcorrection algorithm to create a left separable distortion correctedpixel image from the left raw image and a right separable distortioncorrected pixel image from the right raw image. In an example, amonotonic function f is applied, where f is a 1D transformation function(e.g., f(x)=1+k_1*x{circumflex over ( )}2+k_2*x{circumflex over ( )}4;where x is the horizontal pixel distance from the distortion center andk_1 and k_2 are parameters). The monotonic function prevents the mappedimage from collapsing on itself (e.g., due to 2 pixels being mapped tothe same target). An example of a component-separated correctionalgorithm is shown in Equation 1.:(x _(separabledistortion) , y _(separabledistortion))=r _(x) *x _(raw) ,r _(y) *y _(raw))  (1.)

-   -   where r_(x)=f(x² _(raw)); and        -   r_(y)=f(y² _(raw));    -   wherein x is a pixel location in a horizontal direction and y is        a pixel location in a vertical direction.        As illustrated by Equation 1, in a component separable        correction algorithm, the x component is only affected by        directional components in the x direction (and is not affected        by directional components in the y direction). Likewise, the y        component is only affected by directional components in the y        direction (and is not affected by directional components in the        x direction). This separation of x and y components produces        more realistic looking images than is typically achievable using        conventional techniques. Additionally, the resultant images        better maintain corresponding objects from image pairs in the        same raster, which facilitates detection of the corresponding        objects in determining disparity.

FIG. 8B depicts an illustrative example of a left separable distortioncorrected image 808A corresponding to the left raw image 858A (FIG. 8A)and a right separable distortion corrected image 808B corresponding tothe right raw image 858B (FIG. 8A). During modification, the raw images858A and 858B are transformed into respective separable distortedcorrected images 808A and 808B maintaining pixel scene correspondence inat least the horizontal direction. The distortion may be introduced bythe respective lenses of the left and the right visible light cameras.The distortion caused by the lenses may include producing curvedlines/images where real-world lines/images would be more accuratelyrepresented by straight lines/images. An example of a raw image withdistortion introduced by the lens is illustrated in FIG. 10A and aseparable distortion corrected image is illustrated in FIG. 10B. Asillustrated, the distorted image of FIG. 10A includes aspects (e.g.,roof of the building) which is curved compared to the separabledistortion corrected image of FIG. 10.

At step 606, determine pixel pairs from corresponding image pixelsbetween the left and the right separable distortion corrected images inthe horizontal direction. The processor may determine pixel pairs bycorrelating pixels/objects in the left separable distortion correctedimage 808A with pixels/objects in the right separable distortion image808B. Correspondence may be determined by comparing color and/or imageattributes of one or more pixels (pixel regions, 50 pixels) in the leftimage to one or more pixels in the right image. If the compared colorand/or image attributes of the one or more pixels are identical orwithin a threshold (e.g., 5%) the one or more pixels may be identifiedas a pair.

At step 608, determine corrected disparity correspondence for each ofthe pixel pairs. The processor may determine corrected disparitycorrespondence for each of the pixel pairs by determining the differencein pixel locations of corresponding pixels between the left and rightseparable distortion corrected images and modifying the difference basedon corresponding locations in the respective raw images.

The processor may first determine the difference between correspondingpixel pairs between the left and right separable distortion correctedimages (step 702; FIG. 7). The processor may determine disparity betweenthe separable distortion corrected images by identifying correspondingfeatures in the separable distortion corrected images 808A and 808B anddetermining a number of pixels (typically in the horizontal direction)between a location of a pixel 810B in the right rectified image 808Bcorresponding to where the object pixel 810A appears in the left image808A and where the corresponding object pixel 810C actually appears inthe right image 808B. The processor may determine disparity between therectified images by correlating the rectified images 808A/B anddetermining a number of pixels (typically in the horizontal direction)between a location of a pixel 810B in the right rectified image 808Bcorresponding to where the object pixel 801A appears in the left image808A and where the corresponding object pixel 801C actually appears inthe right image 808B. Correlation of the left and right pixels can beachieved with Semi-Global Block Matching (SGBM), for example. This isillustrated in FIG. 9 where a pixel 810A is shown in solid line in aleft separable distortion corrected image 808A and a representation ofthat same pixel location 810C is shown in dashed line in the rightseparable distortion corrected image 808B. The disparity for the imagepixels in the separable distortion corrected images is the differencebetween the represented pixel location 810C in the right image 808B andthe actual pixel location 810B of the corresponding feature in the rightimage 808B. As illustrated, there may be a minimum expected disparitydue to the distance between the cameras capturing the images.

The processor then determines corrected distortion disparity using thedifference in position of the respective raw pixel pair locationscorresponding to the location of the pixel pairs in the separabledistortion corrected images (step 704; FIG. 7). The processor thenmodifies the disparity correspondence by replacing the separabledistortion disparity with the corrected disparity (step 706; FIG. 7).

At step 610, create a depth map for the scene using the correcteddistortion disparity. In one example, the depth map includes a pluralityof vertices based on the corrected distortion disparity and each vertexincludes one or more of a color attribute or a texture attribute. Theprocessor may calculate a Z location coordinate for each of the verticesof the depth map using the corrected distortion disparity.

At step 612, generate a three dimensional (3D) scene using thedetermined disparity and the corrected images. To create the 3D scene,the processor renders a 3D scene from the left and right separablecomponent corrected images and the depth map. The processor may renderthe 3D scene using image processing 3D rendering programs. Suitable 3Drendering programs will be understood by one of skill in the art fromthe description herein.

At step 614, present the 3D image. In an example, the processor maypresent the 3D scene on a display of the eyewear or a mobile devicecoupled to the eyewear.

In an example, the depth map may be used in computer vision algorithmsthat utilize depth information. For example, the depth map can enable acomputer vision system to understand where hands are positioned in 3Dcoordinates.

Any of the separable distortion disparity determination functionalitydescribed herein for the eyewear device 100, mobile device 990, andserver system 998 can be embodied in one more applications as describedpreviously. According to some embodiments, “function,” “functions,”“application,” “applications,” “instruction,” “instructions,” or“programming” are program(s) that execute functions defined in theprograms. Various programming languages can be employed to create one ormore of the applications, structured in a variety of manners, such asobject-oriented programming languages (e.g., Objective-C, Java, or C++)or procedural programming languages (e.g., C or assembly language). In aspecific example, a third party application (e.g., an applicationdeveloped using the ANDROID™ or IOS™ software development kit (SDK) byan entity other than the vendor of the particular platform) may bemobile software running on a mobile operating system such as IOS™,ANDROID™, WINDOWS® Phone, or another mobile operating systems. In thisexample, the third party application can invoke API calls provided bythe operating system to facilitate functionality described herein.

Hence, a machine-readable medium may take many forms of tangible storagemedium. Non-volatile storage media include, for example, optical ormagnetic disks, such as any of the storage devices in any computer(s) orthe like, such as may be used to implement the client device, mediagateway, transcoder, etc. shown in the drawings. Volatile storage mediainclude dynamic memory, such as main memory of such a computer platform.Tangible transmission media include coaxial cables; copper wire andfiber optics, including the wires that comprise a bus within a computersystem. Carrier-wave transmission media may take the form of electric orelectromagnetic signals, or acoustic or light waves such as thosegenerated during radio frequency (RF) and infrared (IR) datacommunications. Common forms of computer-readable media thereforeinclude for example: a floppy disk, a flexible disk, hard disk, magnetictape, any other magnetic medium, a CD-ROM, DVD or DVD-ROM, any otheroptical medium, punch cards paper tape, any other physical storagemedium with patterns of holes, a RAM, a PROM and EPROM, a FLASH-EPROM,any other memory chip or cartridge, a carrier wave transporting data orinstructions, cables or links transporting such a carrier wave, or anyother medium from which a computer may read programming code and/ordata. Many of these forms of computer readable media may be involved incarrying one or more sequences of one or more instructions to aprocessor for execution.

The scope of protection is limited solely by the claims that now follow.That scope is intended and should be interpreted to be as broad as isconsistent with the ordinary meaning of the language that is used in theclaims when interpreted in light of this specification and theprosecution history that follows and to encompass all structural andfunctional equivalents. Notwithstanding, none of the claims are intendedto embrace subject matter that fails to satisfy the requirement ofSections 101, 102, or 103 of the Patent Act, nor should they beinterpreted in such a way. Any unintended embracement of such subjectmatter is hereby disclaimed.

Except as stated immediately above, nothing that has been stated orillustrated is intended or should be interpreted to cause a dedicationof any component, step, feature, object, benefit, advantage, orequivalent to the public, regardless of whether it is or is not recitedin the claims.

It will be understood that the terms and expressions used herein havethe ordinary meaning as is accorded to such terms and expressions withrespect to their corresponding respective areas of inquiry and studyexcept where specific meanings have otherwise been set forth herein.Relational terms such as first and second and the like may be usedsolely to distinguish one entity or action from another withoutnecessarily requiring or implying any actual such relationship or orderbetween such entities or actions. The terms “comprises,” “comprising,”“includes,” “including,” or any other variation thereof, are intended tocover a non-exclusive inclusion, such that a process, method, article,or apparatus that comprises or includes a list of elements or steps doesnot include only those elements or steps but may include other elementsor steps not expressly listed or inherent to such process, method,article, or apparatus. An element preceded by “a” or “an” does not,without further constraints, preclude the existence of additionalidentical elements in the process, method, article, or apparatus thatcomprises the element.

Unless otherwise stated, any and all measurements, values, ratings,positions, magnitudes, sizes, and other specifications that are setforth in this specification, including in the claims that follow, areapproximate, not exact. Such amounts are intended to have a reasonablerange that is consistent with the functions to which they relate andwith what is customary in the art to which they pertain. For example,unless expressly stated otherwise, a parameter value or the like mayvary by as much as ±10% from the stated amount.

In addition, in the foregoing Detailed Description, it can be seen thatvarious features are grouped together in various examples for thepurpose of streamlining the disclosure. This method of disclosure is notto be interpreted as reflecting an intention that the claimed examplesrequire more features than are expressly recited in each claim. Rather,as the following claims reflect, the subject matter to be protected liesin less than all features of any single disclosed example. Thus, thefollowing claims are hereby incorporated into the Detailed Description,with each claim standing on its own as a separately claimed subjectmatter.

While the foregoing has described what are considered to be the bestmode and other examples, it is understood that various modifications maybe made therein and that the subject matter disclosed herein may beimplemented in various forms and examples, and that they may be appliedin numerous applications, only some of which have been described herein.It is intended by the following claims to claim any and allmodifications and variations that fall within the true scope of thepresent concepts.

What is claimed is:
 1. A separable distortion disparity determinationsystem comprising: an electronic device including: a frame; and a firstcamera and a second camera supported by the frame, wherein the firstcamera is a first visible light camera and has a first viewpoint and thesecond camera is a second visible light camera and has a secondviewpoint separated from the first viewpoint in a camera baselinedirection; an image display; an image display driver coupled to theimage display to control the image display; a memory; a processorcoupled to the first camera, the second camera, the image displaydriver, and the memory; and programming in the memory, wherein executionof the programming by the processor configures the system to performfunctions, including functions to: obtain a first raw pixel image of ascene captured with the first camera; obtain a second raw pixel image ofthe scene captured with the second camera; modify the first and secondraw pixel images using component-separated correction to createrespective first and second corrected pixel images, thecomponent-separated correction maintaining pixel scene correspondence inthe camera baseline direction from between the first and second rawpixel images to between the first and second corrected pixel images,wherein the modify function includes a function to create a firstseparable distortion image from the first raw pixel image and a secondseparable distortion image from the second raw pixel image thatmaintains pixel scene correspondence in at least the camera baselinedirection and removes distortion introduced by respective lens of thefirst and second visible light cameras; determine pixel pairs fromcorresponding pixels between the first and second corrected pixel imagesin the camera baseline direction, wherein the determine pixel pairsfunction includes a function to extract an image disparity bycorrelating pixels in the first separable distortion image with thesecond separable distortion image to calculate a separable distortiondisparity for each of the correlated pixels; and determine disparitycorrespondence for each of the determined pixel pairs from pixellocations in the first and second raw pixel images corresponding torespective pixel locations of the determined pixel pairs in the firstand second corrected pixel images, wherein the determine disparityfunction includes functions to determine respective raw pixel pairlocations in the first and second raw pixel images corresponding tolocations of the determined pixel pairs in the first and secondcorrected pixel images, determine corrected distortion disparity usingthe respective raw pixel pair locations, and replace the separabledistortion disparity with the corrected distortion disparity.
 2. Thesystem of claim 1, wherein: the first camera is a first visible lightcamera configured to capture the first raw pixel image, the first rawpixel image including a first matrix of pixels; and the second camera isa second visible light camera configured to capture the second raw pixelimage, the second raw pixel image including a second matrix of pixels.3. A separable distortion disparity determination system comprising: anelectronic device including: a frame; and a first camera and a secondcamera supported by the frame, wherein the first camera is a firstvisible light camera that has a first viewpoint and the second camera isa second visible light camera that has a second viewpoint separated fromthe first viewpoint in a camera baseline direction; an image display; animage display driver coupled to the image display to control the imagedisplay; a memory; a processor coupled to the first camera, the secondcamera, the image display driver, and the memory; and programming in thememory, wherein execution of the programming by the processor configuresthe system to perform functions, including functions to: obtain a firstraw pixel image of a scene captured with the first camera; obtain asecond raw image of the scene captured with the second camera; modifythe first and second raw pixel images using component-separatedcorrection to create respective first and second corrected pixel images,the component-separated correction maintaining pixel scenecorrespondence in the camera baseline direction from between the firstand second raw pixel images to between the first and second correctedpixel images, wherein the modify function includes a function to createa first separable distortion image from the first raw pixel image and asecond separable distortion image from the second raw pixel image thatmaintains pixel scene correspondence in at least the camera baselinedirection and removes distortion introduced by respective lens of thefirst and second visible light cameras; determine pixel pairs fromcorresponding pixels between the first and second corrected pixel imagesin the camera baseline direction; and determine disparity correspondencefor each of the determined pixel pairs from pixel locations in the firstand second raw pixel images corresponding to respective pixel locationsof the determined pixel pairs in the first and second corrected pixelimages, wherein the function to create the first and second separabledistortion images applies a monotonic function f as follows:(x _(separabledistortion) , y _(separabledistortion))=(r _(x) *x _(raw), r _(y) *y _(raw)) where r_(x)=f(x² _(raw)); and r_(y)=f(y² _(raw));wherein x is a pixel location in a horizontal direction and y is a pixellocation in a vertical direction.
 4. The system of claim 1, wherein thefunctions further include a function to: create a depth map for thescene using the corrected distortion disparity.
 5. The system of claim4, wherein the depth map includes a plurality of vertices based on thecorrected distortion disparity and wherein each vertex includes one ormore of a color attribute or a texture attribute.
 6. The system of claim4, wherein the function to create a depth map including a function to:calculate a Z location coordinate for each vertices of the depth mapusing the corrected distortion disparity.
 7. The system of claim 6,wherein the functions further include functions to: generate a threedimensional scene using the depth map; and present the three dimensionalscene on the image display.
 8. A separable distortion disparitydetermination method comprising the steps of: obtaining a first rawpixel image of a scene from a first viewpoint captured with a firstcamera of an electronic device, wherein the first camera is a firstvisible light camera; obtaining a second raw pixel image of the scenefrom a second viewpoint captured with a second camera of the electronicdevice, the first viewpoint separated from the second viewpoint in acamera baseline direction, wherein the second camera is a second visiblelight camera; modifying the first and second raw pixel images usingcomponent-separated correction to create respective first and secondcorrected pixel images, the component-separated correction maintainingpixel scene correspondence in the camera baseline direction from betweenthe first and second raw pixel images to between the first and secondcorrected pixel images, wherein the modifying step includes creating afirst separable distortion image from the first raw pixel image and asecond separable distortion image from the second raw pixel image thatmaintains pixel scene correspondence in at least the camera baselinedirection and removes distortion introduced by respective lens of thefirst and second visible light cameras; determining pixel pairs fromcorresponding pixels between the first and second corrected pixel imagesin the camera baseline direction, wherein the step to determine pixelpairs includes extracting an image disparity by correlating pixels inthe first separable distortion image with the second separabledistortion image to calculate a separable distortion disparity for eachof the correlated pixels; and determining disparity correspondence foreach of the determined pixel pairs from pixel locations in the first andsecond raw pixel images corresponding to respective pixel locations ofthe determined pixel pairs in the first and second corrected pixelimages, wherein the step of determining disparity includes determiningrespective raw pixel pair locations in the first and second raw pixelimages corresponding to locations of the determined pixel pairs in thefirst and second corrected pixel images, determining correcteddistortion disparity using the respective raw pixel pair locations, andreplacing the separable distortion disparity with the correcteddistortion disparity.
 9. The method of claim 8, wherein the first cameraof the electronic device is a first visible light camera and the secondcamera of the electronic device is a second visible light camera, themethod further comprising the steps of: capturing the first raw pixelimage with the first visible light camera of the electronic device, thefirst raw pixel image including a first matrix of pixels; and capturingthe second raw pixel image with the second visible light camera of theelectronic device, the second raw pixel image including a second matrixof pixels.
 10. A separable distortion disparity determination methodcomprising the steps of: obtaining a first raw pixel image of a scenefrom a first viewpoint captured with a first camera of an electronicdevice, wherein first camera is a first visible light camera; obtaininga second raw pixel image of the scene from a second viewpoint capturedwith a second camera of the electronic device, the first viewpointseparated from the second viewpoint in a camera baseline direction,wherein the second camera is a second visible light camera; modifyingthe first and second raw pixel images using component-separatedcorrection to create respective first and second corrected pixel images,the component-separated correction maintaining pixel scenecorrespondence in the camera baseline direction from between the firstand second raw pixel images to between the first and second correctedpixel images, wherein the modifying comprises creating a first separabledistortion image from the first raw pixel image and a second separabledistortion image from the second raw pixel image that maintains pixelscene correspondence in at least the camera baseline direction andremoves distortion introduced by respective lens of the first and secondvisible light cameras; determining pixel pairs from corresponding pixelsbetween the first and second corrected pixel images in the camerabaseline direction; and determining disparity correspondence for each ofthe determined pixel lairs from pixel locations in the first and secondraw pixel images corresponding to respective pixel locations of thedetermined pixel pairs in the first and second corrected pixel images,wherein the creating step comprises applying to the first and second rawpixel images a monotonic function f as follows:(x _(separabledistortion) , y _(separabledistortion))=(r _(x) *x _(raw), r _(y) *y _(raw)) where r_(x)=f(x² _(raw)); and r_(y)=f(y² _(raw));wherein x is a pixel location in a horizontal direction and y is a pixellocation in a vertical direction.
 11. The method of claim 8, furthercomprising: creating a depth map for the scene using the correcteddistortion disparity.
 12. The method of claim 11, wherein the depth mapincludes a plurality of vertices based on the corrected distortiondisparity and wherein each vertex includes one or more of a colorattribute or a texture attribute.
 13. The method of claim 11, whereinthe creating step comprises: calculating a Z location coordinate foreach vertices of the depth map using the corrected distortion disparity.14. The method of claim 11, further comprising: generating a threedimensional scene using the depth map; and presenting the threedimensional scene on a display of the electronic device or a remotedisplay of a remote portable device coupled to the electronic device.